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Jizhao Wang, Yunyi Liang, Jinjun Tang and Zhizhou Wu
This research contributes to the development of a technological method to obtain highly accurate vehicle trajectory data. The reconstructed trajectory data play a key role in traffic state prediction, traffic management and the decision making of autonom...
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Carlos Alfonso Zafra-Mejía, Hugo Alexander Rondón-Quintana and Carlos Felipe Urazán-Bonells
The objective of this paper is to use autoregressive, integrated, and moving average (ARIMA) and transfer function ARIMA (TFARIMA) models to analyze the behavior of the main water quality parameters in the initial components of a drinking water supply sy...
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Yin Tang, Lizhuo Zhang, Dan Huang, Sha Yang and Yingchun Kuang
In view of the current problems of complex models and insufficient data processing in ultra-short-term prediction of photovoltaic power generation, this paper proposes a photovoltaic power ultra-short-term prediction model named HPO-KNN-SRU, based on a S...
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Saikat Das, Mohammad Ashrafuzzaman, Frederick T. Sheldon and Sajjan Shiva
The distributed denial of service (DDoS) attack is one of the most pernicious threats in cyberspace. Catastrophic failures over the past two decades have resulted in catastrophic and costly disruption of services across all sectors and critical infrastru...
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Woo-Hyun Choi and Jung-Ho Lewe
This study proposes a deep learning model utilizing the BACnet (Building Automation and Control Network) protocol for the real-time detection of mechanical faults and security vulnerabilities in building automation systems. Integrating various machine le...
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Liqiu Chen, Chongshi Gu, Sen Zheng and Yanbo Wang
Real and effective monitoring data are crucial in assessing the structural safety of dams. Gross errors, resulting from manual mismeasurement, instrument failure, or other factors, can significantly impact the evaluation process. It is imperative to elim...
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Károly Héberger
Background: The development and application of machine learning (ML) methods have become so fast that almost nobody can follow their developments in every detail. It is no wonder that numerous errors and inconsistencies in their usage have also spread wi...
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Fan Lin, Dengjie Chen, Cheng Liu and Jincheng He
This study pioneered a non-destructive testing approach to evaluating the physicochemical properties of golden passion fruit by developing a platform to analyze the fruit?s electrical characteristics. By using dielectric properties, the method accurately...
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Shengwei Jia, Nianyu Zou, Songhai Xu and Min Cheng
In this paper, an illumination measurement system is proposed and experimentally demonstrated. The system consists of two parts, including the illumination acquisition module mounted on the UAV and the real-time display interface of the cloud platform wi...
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Cindy Trinh, Silvia Lasala, Olivier Herbinet and Dimitrios Meimaroglou
This article investigates the applicability domain (AD) of machine learning (ML) models trained on high-dimensional data, for the prediction of the ideal gas enthalpy of formation and entropy of molecules via descriptors. The AD is crucial as it describe...
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